Volume 37 Issue 9
Sep.  2012
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HE Zhengbin, NIE Jianliang, WU Fumei, ZHANG Juqing. Kalman Filtering Algorithm Based on Random Design Matrices with Application to Integrated GNSS/INS Navigation[J]. Geomatics and Information Science of Wuhan University, 2012, 37(9): 1036-1040.
Citation: HE Zhengbin, NIE Jianliang, WU Fumei, ZHANG Juqing. Kalman Filtering Algorithm Based on Random Design Matrices with Application to Integrated GNSS/INS Navigation[J]. Geomatics and Information Science of Wuhan University, 2012, 37(9): 1036-1040.
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Kalman Filtering Algorithm Based on Random Design Matrices with Application to Integrated GNSS/INS Navigation

  • 1 School of Geological and Surveying Engineering,Chang'an University,126 Yanta Road,Xi'an 710054,China;2 Geodetic Data Processing Center,National Administration of Surveying,Mapping and Geoinformation, 334 East Youyi Road,Xi'an 710054,China;3 Institute of Surveying and Mapping,Information Engineering University,66 Middle Longhai Road,Zhengzhou 450052,China;4 Xi'an Research Institute of Surveying and Mapping,1 Middle Yanta Road,Xi'an 710054,China;5 Key Laboratory of Western China's Mineral Resources and Geological Engineering, Ministry of Education,126 Yanta Road,Xi'an 710054,China

Funds: 国家自然科学基金资助项目(41020144004,41004013);;中央高校基本科研业务费资助项目(CHD2010JC048);;长安大学基础研究支持计划专项基金资助项目;;西部矿产资源与地质工程教育部重点实验室开放基金资助项目
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  • Received Date: June 19, 2012
  • Published Date: September 04, 2012
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    • Abstract
  • Kalman filter is widely used in the area of kinematic positioning and navigation.However,it doesn′t have the ability to resist the influence of measurement outliers,hence its performance is easy impacted by the observation outliers or kinematic state disturbing.In order to guarantee the reliability of the navigation with precise dynamic model,a model set,which contains many different observation models,is established.An improved Kalman filtering,in which the design matrix of the observational model is substituted by its expectation is proposed to control the influences of the measurement outliers.An integrated GPS/INS navigation example is given to show that the modified Kalman filtering algorithm works well.
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